Downside Risk for the "New" GM

The new post-bailout, post-bankrupt GM has been generating some buzz on Wall Street this week. Yesterday, its stock jumped 2.8% in premarket trading after investment groups initiated coverage on the new stock. Credit Suisse gave the new GM an "Outperform" rating and a $43 per share price target (the stock was at 36.0 at the end of trading, see above). JP Morgan gave it an "Overweight" and a $44 price target while RBC Capital Markets set an "Outperform" rating. What should we think about this enthusiasm for "Government Motors." Is it just more "Irrational Exuberance"?
Let' s look at what history can tell us. In the time series above I've spliced together the old GM stock price history (MTLQQ.PK) with the new stock (GM) after the IPO in November. The red dotted line displays the one-step ahead predictions for the best fit model [1] to the stock trend. The best-fit model is a random walk, that is, today is like tomorrow except for random shocks! A "Random Walk Down Wall Street," indeed!
That's a surprise result for the world's largest multinational automaker, the engine of growth for the post-War U.S. economy [2]. The graph above shows a plot of the GM random walk model without the random shocks. Until mid-2005 (the beginning of the end?), the stock price did not stray far from it's initial value in the 1960s. What should we expect for the future?
"More of the same" would be a good guess. The graph above shows the random-walk forecast for 2011 with confidence intervals. What this shows is that any stock price between 10 and 50 is probable (within the 98% confidence interval for a random walk). The price targets from the investment groups seem a little more conservative. What's also interesting is that the investment houses don't talk about the downside risk.

My opinion: stocks that are random walks without even some observable drift are best left to the investment houses. Supposedly, the "smart money" can anticipate shocks and trigger events in ways that the average investor cannot. But, what do I know. I'm not even the 800-pound gorilla in the room!

[1] To find the best fit model, I used some statistical techniques to search among various candidate models ranging from business-as-usual models to models based on a broad index of secular and cyclical performance in the U.S. economy. None of these models fit any better than a random walk. The result doesn't mean that at some time in the future I won't find a model that outperforms the random walk.

[2] Some of the choppiness is due to stock splits. GM has had three stock splits since 1950, including a 2-for-1 split in October 1950, a 3-for-1 split in September 1955 and a 2-for-1 split in March 1989. The company has also adjusted its stock after spinning off subsidies such as Hughes and Delphi.

The Wizard of Oz Was A Fraud

The was a great Op-Ed piece in a recent NY Times by one of Bernie Madoff's investors (not many of them have, understandably, said much). Michael Kubin gives his hard-won lessons for investors:

Make sure the accountants are reputable, the results transparent, insist on meeting the managers in person. Keep in mind that risk and reward always travel together, that if something sounds too good to be true it usually is, that the law of gravity cannot be repealed, that you’re seldom warned the floor has just been waxed. Remember the Wizard of Oz was a phony.

Lesson learned! Unfortunately, the lessons were draw from the well-known words of Lord Polonius in the Tragedy of Hamlet:

And these few precepts in thy memory
See thou character. Give thy thoughts no tongue,
Nor any unproportioned thought his act.
Be thou familiar, but by no means vulgar.
Those friends thou hast, and their adoption tried,
Grapple them to thy soul with hoops of steel;
But do not dull thy palm with entertainment
Of each new-hatch'd, unfledged comrade. Beware
Of entrance to a quarrel, but being in,
Bear't that the opposed may beware of thee.
Give every man thy ear, but few thy voice;
Take each man's censure, but reserve thy judgment.
Costly thy habit as thy purse can buy,
But not express'd in fancy; rich, not gaudy;
For the apparel oft proclaims the man,
And they in France of the best rank and station
Are of a most select and generous chief in that.
Neither a borrower nor a lender be;
For loan oft loses both itself and friend,
And borrowing dulls the edge of husbandry.
This above all: to thine ownself be true,
And it must follow, as the night the day,
Thou canst not then be false to any man.
Farewell: my blessing season this in thee!

The 1939 movie The Wizard of Oz was, of course, made during the Great Depression.

Global Warming: Why Are The Winters Getting Colder?

In today's NY Times, seasonal weather forecaster Judah Cohen explains (here) how the Earth system can warm at the same time that winters in the Northern Hemisphere (NH) become cooler. Cohen also points out some problems in long-term weather forecasts and the Global Circulation Models (GCMs) used to predict climate change.

Here's the causal explanation (see the directed graph on the right): Global warming increases Arctic sea ice melt. As the sea ice melts, more moisture is released into the atmosphere. More moisture means that there will be more snow in Siberia. As snow cover increases, more energy is reflected back to space (the Earth's albedo or "whiteness" increases and white objects reflect more energy).

As more energy is reflected back to space, an Arctic cold air dome forms over Siberia. The large dome of cold air shifts the jet stream from its normal West-to-East direction to a more North-South oscillation. As the Jet stream moves from North to South it acquires Southern moisture and pulls down Northern Canadian cold air (in the US).

The predictions from Cohen's model for the U.S. (displayed at right) show that the Northeastern U.S. was predicted to be colder than usual while the Southern U.S. was predicted to be warmer. The actual trends (lower graphic) were very close to the model's predictions.

Long-term weather forecasts are largely based on the El Nino/La Nina-Southern Oscillation (ENSO). Warming or cooling of the tropical Pacific Ocean on a five-year cycle cause weather disturbances for the entire planet. Since the oscillation is quasi-deterministic and since the effects of the oscillation on weather are known from historical data, long-term weather prediction is possible. The current long-term forecasts do not take into account Siberian snow fall and neither do the GCMs that are used to predict global warming. We can expect some improvements in forecasting and climate change predictions as ENSO and the Arctic snow cycle are better understood.

Expansion of Government: Federal Employment

In today's NY Times (here) Paul Krugman points out that Republican presidential candidates have made a campaign theme out of expansion of the Federal government and particularly the expansion of the federal workforce. The data [1] [2] and a naive forecast are displayed above (read a fact check of outgoing Minnesota governor Tim Pawlenty's numbers here).

Federal employment has actually been decreasing since the Vietnam War. The small expansion during 2010 was purely a result of the temporary employment of census workers. Unfortunately, the naive forecast above is not very realistic.
Federal employment is probably too low right now as shown by the forecast confidence intervals above. Given world military events, increasing threats to homeland security and increasing need for financial regulation based on the global financial crisis, there is nowhere to go but up for Federal employment. The expansion will be a continuing source of campaign rhetoric during the next presidential cycle.

[1] The data can be found here.

[2] Data comes from agency 113 monthly submissions and covers total end-of-year civilian employment of full-time permanent, temporary, part-time, and intermittent employees. Executive branch includes the Postal Service, and, beginning in 1970, includes various disadvantaged youth and worker-trainee programs. Uniformed Military Personnel data comes from the Department of Defense.

EIA Projects Climate Catastrophe?

The US Energy Information Agency (EIA) published an early release of the 2011 Annual Energy Outlook (here). In the report, the EIA projects that energy-related CO2 emissions will grow by 16% from 2009 to 2035 to a level of 6.3 billion metric tons of carbon dioxide equivalent (1.7 GtC0). The non-skeptic climate blogs (here and here) are calling the projections a "catastrophe," except that the EIA projections are usually wrong (the EIA's own evaluations of their forecasts are here): (1) they assume the future will be like the past, (2) they don't model policy changes, (3) they underestimate the role of technology (reductions in emission intensity), and (4) have ignored the possible effects of peak oil.

To this list, I would add that the EIA published no confidence intervals with the projection (see my forecast with confidence intervals here). In a well-constructed model, the confidence intervals account for the probabilistic effects of unanticipated changes in the future. The factors that might avert catastrophe and can be anticipated, should be built into models (a brief and completely inadequate discussion of the IEO2010 models can be found here).

Even with anticipated future changes that might reduce carbon emissions, solutions based on policy wedges (here) require a "...staggering amount of effort by both private and public sectors" if we are to keep the economy growing while at the same time reducing carbon emissions. Reducing economic growth rates, which clearly in both the EIA and my own projections did happen as a result of the global financial crisis, would provide the breathing room to implement policy wedges.

Unfortunately, our only thought right now is to get out of the global financial crisis and return to a level of "robust economic growth" and, as a result, robust CO2 emissions.

Controlling Carbon Emissions

On November 10, 2010 Nature published an article updating CO2 emissions for the world. The article noted that "global CO2 emissions from fossil fuel burning decreased by 1.3% in 2009 owing to the global financial and economic crisis that started in 2008; this is half the decrease anticipated a year ago." In other words, if there is any doubt about the link between CO2 emissions and economic growth, the global financial crisis provided a natural experiment proving the link. It's very difficult (OK, impossible) to run experiments on the world system, so the result is an important finding.

The study goes on to note that once the global financial crisis is over, the economy is expected to resume growing (the IMF, here, expects the global economy to grow by 4.8% in 2010) and emitting at the same pace. The only hope for reducing carbon emissions then is to reduce the carbon intensity of the global economy, that is, quickly shift to low-carbon forms of energy (solar, wind, nuclear, etc.). To me, the shift seems unlikely (cars, buses, trucks and trains are unlikely to run on low-carbon fuel any time in the near future--even all-electric cars will run on energy from coal-fired power plants).

But, the global financial crisis may have been a blessing in disguise, at least for climate change. The time series graph above (the y-axis is CO2 emissions in PgC per year for fossil fuel burning and cement manufacturing) takes the new emission data from the Nature study and forecasts it out to 2020 assuming that the world economy grows by 4%. Although the financial bubble and collapse are clear from the data (and are predicted quite well by the model), the future growth of emission is relatively flat. Small reductions in economic growth would go a long way to stabilizing CO2 emissions. Experience with the financial bubble just might lead to more modest growth than the IMF anticipates. And, slower growth would provide some breathing room to reduce the carbon intensity of the global economy.

The Nature article also has updated analysis of the global carbon cycle. I'll analyze some of that in future posts.